Robert Krajewski

1.9k total citations · 1 hit paper
16 papers, 1.2k citations indexed

About

Robert Krajewski is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Robert Krajewski has authored 16 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Automotive Engineering, 7 papers in Computer Vision and Pattern Recognition and 4 papers in Control and Systems Engineering. Recurrent topics in Robert Krajewski's work include Autonomous Vehicle Technology and Safety (13 papers), Traffic and Road Safety (3 papers) and Advanced Neural Network Applications (3 papers). Robert Krajewski is often cited by papers focused on Autonomous Vehicle Technology and Safety (13 papers), Traffic and Road Safety (3 papers) and Advanced Neural Network Applications (3 papers). Robert Krajewski collaborates with scholars based in Germany, Switzerland and Poland. Robert Krajewski's co-authors include Lutz Eckstein, Julian Bock, Laurent Kloeker, Tobias Moers, Adrian Zlocki, Jens Klimke, Marek Kozłowski and Henryk Rybiński and has published in prestigious journals such as Traffic Injury Prevention, Journal of Intelligent Information Systems and ATZ - Automobiltechnische Zeitschrift.

In The Last Decade

Robert Krajewski

15 papers receiving 1.2k citations

Hit Papers

The highD Dataset: A Drone Dataset of Naturalistic Vehicl... 2018 2026 2020 2023 2018 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Robert Krajewski Germany 8 947 487 367 276 244 16 1.2k
Julian Bock Germany 10 958 1.0× 482 1.0× 392 1.1× 282 1.0× 244 1.0× 17 1.2k
Laurent Kloeker Germany 4 699 0.7× 370 0.8× 280 0.8× 207 0.8× 182 0.7× 6 881
Dizan Vasquez France 10 857 0.9× 371 0.8× 290 0.8× 243 0.9× 571 2.3× 18 1.3k
Tim A. Wheeler United States 9 565 0.6× 331 0.7× 190 0.5× 206 0.7× 186 0.8× 12 841
Erik Coelingh Sweden 16 1.0k 1.1× 698 1.4× 284 0.8× 150 0.5× 254 1.0× 30 1.4k
Tobias Gindele Germany 15 713 0.8× 338 0.7× 148 0.4× 150 0.5× 337 1.4× 16 977
Gabi Breuel Germany 13 655 0.7× 238 0.5× 212 0.6× 202 0.7× 205 0.8× 24 785
Mattias Brännström Sweden 12 770 0.8× 486 1.0× 199 0.5× 104 0.4× 201 0.8× 22 897
Arda Kurt United States 15 729 0.8× 587 1.2× 123 0.3× 169 0.6× 168 0.7× 43 981
Nico Kaempchen Germany 15 674 0.7× 258 0.5× 132 0.4× 117 0.4× 329 1.3× 20 1.0k

Countries citing papers authored by Robert Krajewski

Since Specialization
Citations

This map shows the geographic impact of Robert Krajewski's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Robert Krajewski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Krajewski more than expected).

Fields of papers citing papers by Robert Krajewski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert Krajewski. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Robert Krajewski. The network helps show where Robert Krajewski may publish in the future.

Co-authorship network of co-authors of Robert Krajewski

This figure shows the co-authorship network connecting the top 25 collaborators of Robert Krajewski. A scholar is included among the top collaborators of Robert Krajewski based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Robert Krajewski. Robert Krajewski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Moers, Tobias, et al.. (2022). The exiD Dataset: A Real-World Trajectory Dataset of Highly Interactive Highway Scenarios in Germany. 2022 IEEE Intelligent Vehicles Symposium (IV). 958–964. 71 indexed citations
2.
Krajewski, Robert, et al.. (2021). Drone-based Generation of Sensor Reference and Training Data for Highly Automated Vehicles. 3067–3074. 1 indexed citations
4.
Bock, Julian, et al.. (2021). Hochgenaue Szenarien- und Referenzdaten für das automatisierte Fahren. ATZ - Automobiltechnische Zeitschrift. 123(5-6). 50–55.
5.
Bock, Julian, et al.. (2021). Highly Accurate Scenario and Reference Data for Automated Driving. ATZ worldwide. 123(5-6). 50–55. 7 indexed citations
7.
Krajewski, Robert, et al.. (2020). The rounD Dataset: A Drone Dataset of Road User Trajectories at Roundabouts in Germany. 1–6. 133 indexed citations
8.
Krajewski, Robert, et al.. (2020). Using drones as reference sensors for neural-networks-based modeling of automotive perception errors. 708–715. 6 indexed citations
11.
Bock, Julian, et al.. (2019). A framework for definition of logical scenarios for safety assurance of automated driving. Traffic Injury Prevention. 20(sup1). S65–S70. 42 indexed citations
13.
Krajewski, Robert, Julian Bock, Laurent Kloeker, & Lutz Eckstein. (2018). The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems. 2118–2125. 861 indexed citations breakdown →
14.
15.
Krajewski, Robert, Henryk Rybiński, & Marek Kozłowski. (2015). A novel method for dictionary translation. Journal of Intelligent Information Systems. 47(3). 491–514. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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